. β-Amyloid discordance of cerebrospinal fluid and positron emission tomography imaging shows distinct spatial tau patterns. Brain Commun. 2022;4(2):fcac084. Epub 2022 Mar 31 PubMed.

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  1. Both our paper and the Lee et al. paper tackle complementary questions relating to tau spread. While our study demonstrates that about 9 percent of clinically unimpaired individuals with abnormal Aβ have divergent cortical tau patterns, Lee et al. investigated the important question of how amyloid triggers tau spread when amyloid and tau follow different spatial patterns of spread, i.e., amyloid begins in the neocortex and spreads into the entorhinal cortex in Phase 2 (Thal et al., 2002), while tau begins in the transentorhinal region and spreads to entorhinal cortex and eventually neocortex (Braak et al., 2006).

    Lee et al. provide evidence for both remote and local amyloid-tau interactions, such that first there are remote interactions between cortical amyloid and entorhinal tau that promote tangle spread to nearby regions connected to entorhinal cortex, then tau deposits reach the inferior temporal gyrus where they locally interact with amyloid for the first time. Finally, tangles spread into amyloid-positive neocortical regions that are connected to the inferior temporal gyrus.

    That Lee et al. identify the inferior temporal gyrus as a key region for amyloid-tau interactions is intriguing, given that our study also suggested that inferior temporal, lateral parietal, and precuneus may be especially vulnerable areas for early tau deposition. Indeed, consistent with our suggestion, Figure 4B in the Lee et al. paper shows that lateral parietal and precuneus, in addition to inferior temporal gyrus, also show high local and remote amyloid and tau interactions. Together, our studies highlight the importance of these regions in models of Alzheimer’s disease progression.

    Lee et al. also noted that not all participants with early Alzheimer’s disease conformed to their spreading framework, highlighting the existence of heterogeneity across individuals. These non-conforming participants may indeed be the ones with divergent cortical tau patterns highlighted in our study. The same remote and local amyloid-tau interactions identified by Lee et al. may be occurring in those with divergent cortical tau, but the specific location of amyloid-tau interactions may vary outside of the entorhinal cortex, leading to the spatial heterogeneity that we and others (Vogel et al., 2021) have described.

    This model would provide an explanation for the known heterogeneity observed in various clinical presentations of Alzheimer’s disease (Ossenkoppele et al., 2016). In other words, the mechanisms related to local and remote amyloid-tau interactions could be similar across clinical presentations of Alzheimer’s disease, but individual differences in cortical hub regions could result in heterogeneous patterns of tau spread, which could in turn give rise to different clinical symptom profiles. The reasons why this heterogeneity occurs beyond entorhinal cortex remains unknown and is a key unanswered gap in Alzheimer’s disease research.

    References:

    . Phases of A beta-deposition in the human brain and its relevance for the development of AD. Neurology. 2002 Jun 25;58(12):1791-800. PubMed.

    . Staging of Alzheimer disease-associated neurofibrillary pathology using paraffin sections and immunocytochemistry. Acta Neuropathol. 2006 Oct;112(4):389-404. PubMed.

    . Four distinct trajectories of tau deposition identified in Alzheimer's disease. Nat Med. 2021 May;27(5):871-881. Epub 2021 Apr 29 PubMed.

    . Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer's disease. Brain. 2016 May;139(Pt 5):1551-67. Epub 2016 Mar 8 PubMed.

    View all comments by Christina Young
  2. These interesting papers deal with important questions regarding the spatial and temporal discrepancies between amyloid and tau that appeal to mechanisms that relate to the functional architecture of the brain. The authors are also trying to integrate the well-known phenomenon of phenotypic heterogeneity in clinical presentations, structural imaging, molecular imaging, functional imaging, and pathology (Graff-Radford et al., 2021).

    These are topics we have previously synthesized within the cascading network failure model of Alzheimer’s disease and subsequently investigated in aging and across AD phenotypes (Jones et al., 2017; Jones et al., 2016; Sintini et al., 2021Wiepert et al., 2017). In our studies, we use functional connectivity measures from patients rather than using templates from healthy controls, which allows for a different view of the functional physiology and its relationship to amyloid and tau reported in most studies. Our model emphasizes distributed functional physiology in ensembles of cells spanning large-scale anatomy associated with mental functions, or the global functional state space (GFSS) (Jones et al., 2022). In our study of the GFSS, we observed that there is a relatively simple relationship between mental functions and brain anatomy that can predict many aspects of Alzheimer’s physiology, including Braak staging of tau neurofibrillary tangle pathology. This underlying functional organization may drive many of the relationships reported in associative neuroimaging studies using large-scale anatomic patterns across all degenerative disease that cause dementia. That is why we were also able to relate this simple brain-behavior mapping to large-scale brain networks, mental task activation patterns, and a diverse array of clinical syndromes that span the dementia spectrum. In our model, large scale neurodynamics that take place across the landscape of the GFSS is the key element that links functional physiology to selective patterns of degenerative anatomy. In this model, neurodegenerative selectivity for certain dynamic brain patterns, or modes of function of the complex information processing system in the brain, requires a fundamental role for large-scale neurodynamic physiology in AD and related disorders.

    These functional dynamics that influence cellular activity across large ensembles of cells may contribute to homeostatic failure in protein processing physiology. This is consistent with an accelerated failure time model of amyloid and tau (Therneau et al., 2021). This alternative view of the relationship between amyloid, tau, and functional brain organization suggests different biomarkers and therapeutic targets related to large-scale functional physiology that can complement existing models focused more on molecular behavior.

    References:

    . New insights into atypical Alzheimer's disease in the era of biomarkers. Lancet Neurol. 2021 Mar;20(3):222-234. PubMed.

    . Tau, amyloid, and cascading network failure across the Alzheimer's disease spectrum. Cortex. 2017 Dec;97:143-159. Epub 2017 Oct 3 PubMed.

    . Cascading network failure across the Alzheimer's disease spectrum. Brain. 2016 Feb;139(Pt 2):547-62. Epub 2015 Nov 19 PubMed.

    . Tau and Amyloid Relationships with Resting-state Functional Connectivity in Atypical Alzheimer's Disease. Cereb Cortex. 2021 Feb 5;31(3):1693-1706. PubMed.

    . A robust biomarker of large-scale network failure in Alzheimer's disease. Alzheimers Dement (Amst). 2017;6:152-161. Epub 2017 Jan 25 PubMed.

    . A computational model of neurodegeneration in Alzheimer's disease. Nat Commun. 2022 Mar 28;13(1):1643. PubMed.

    . Relationships between β-amyloid and tau in an elderly population: An accelerated failure time model. Neuroimage. 2021 Nov 15;242:118440. Epub 2021 Jul 29 PubMed.

    View all comments by David Jones

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